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Hybrid Automaton Based Vehicle Platoon Modelling and Cooperation Behaviour Profile Prediction

机译:基于混合自动机的汽车排建模与协同行为轮廓预测

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Autonomous cooperative driving systems require the integration of research activities in the field of embedded systems, robotics, communication, control and artificial intelligence in order to create a secure and intelligent autonomous drivers behaviour patterns in the traffic. Beside autonomous vehicle management, an important research focus is on the cooperation behaviour management. In this paper, we propose hybrid automaton modelling to emulate flexible vehicle Platoon and vehicles cooperation interactions. We introduce novel coding function for Platoon cooperation behaviour profile generation in time, which depends of vehicles number in Platoon and behaviour types. As the behaviour prediction of transportation systems, one of the primarily used methods of artificial intelligence in Intelligent Transport Systems, we propose an approach towards NARX neural network prediction of Platoon cooperation behaviour profile. With incorporation of Platoon manoeuvres dynamic prediction, which is capable of analysing traffic behaviour, this approach would be useful for secure implementation of real autonomous vehicles cooperation.
机译:自主协作驾驶系统需要集成嵌入式系统,机器人技术,通信,控制和人工智能领域的研究活动,以便在交通中创建安全和智能的自主驾驶员行为模式。除了自动驾驶汽车管理外,重要的研究重点还在于合作行为管理。在本文中,我们提出了混合自动机建模,以模拟灵活的车辆排和车辆协作交互。我们引入了用于排协同行为简档及时生成的新颖编码功能,该功能取决于排中的车辆数量和行为类型。作为交通运输系统的行为预测,这是智能交通运输系统中人工智能的主要使用方法之一,我们提出了一种对NARX神经网络进行排队协作行为预测的方法。结合能够对交通行为进行分析的排机动动态预测,该方法对于安全实施真正的自动驾驶汽车合作将很有用。

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